Nonlinear Optimal Control and Differential Flatness for Renewable Energy Systems and EVs in the Smart Grid

Nonlinear Optimal Control and Differential Flatness for Renewable Energy Systems and EVs in the Smart Grid addresses the need for developing and implementing nonlinear control, estimation, and fault diagnosis methods, to enable the integration of renewable energy resources in the power grid as well as the optimization of power management in electric vehicles. The book targets several technical challenges, including intelligent control of electric machines and of power electronics, fault tolerant control and fault diagnosis for renewable energy systems and EVs, nonlinear control for synchronization of the electricity grid, and computational intelligence techniques for electric power. The dynamic models of new configurations of distributed and interconnected renewable energy systems, as well as those of new forms of powertrains of electric vehicles, are characterized by unique controllability, observability and detectability properties, with the potential to reach genuine and impactful results. This is of interest to researchers, graduate students, and faculty across renewable energy, electrical engineering, computer science, power systems, power electronics, electric vehicles, and transportation systems, as well as engineers working on control problems and estimation methods, and skilled technical personnel working on real applications.

• Combines advanced control and fault diagnosis methods for renewable energy systems and EVs
• Draws on cutting-edge research to present novel nonlinear control methods
• Bridges the gap between theoretical aspects and control systems in renewable energy applications